Data Integration, Mass Spectrometry Proteomics Software Development

Overview
Quantitative proteomics
Data integration in kinetic modelling in systems biology

A typical proteomics experiment
Various routes through this map
Separating by size or charge in most cases Identify peptides as a proxy for proteins, comparing theoretical to experimental spectra

Approach described is qualitative
Peptides / proteins identified but not quantified
Mass spectrometry is not quantitative per se
Different compounds have different physiochemical properties
May ionise differently, more / less readily
Therefore peak intensities cannot be compared between two different compounds
Applies to peptides / proteins

BUT peak intensities can be compared between compounds sharing the same physiochemical properties
Isotopes
Same physiochemical properties
Different molecular masses (ΔM = 6Da)

Can apply the same principle for peptides :
IDVAVDSTGVFK
IDVAVDSTGVF K*
Lysine (K) residue is labelled with C 13
Same physiochemical properties
Different molecular masses (ΔM = 6Da)

Absolute quantitative proteomics requires isotopically-labelled peptide of known concentration spiked into sample
Isotopically-identical peptides behave consistently
Comparable peak intensity, comparable retention time
Ratio of labelled over non-labelled peptide can be used to determined absolute concentration of sample peptide

Mixture 40:60 Data: Kathleen Carroll (Orbitrap MS) Quantitative proteomics: QconCAT

Quantitative proteomics: QconCAT
Requirements:
Determine absolute protein concentrations under a given cellular condition
Quantify a number (~50) proteins simultaneously
Apply QconCAT methodology
Allows simultaneous introduction of many labelled peptides into sample
Multiplexed absolute quantification for proteomics using concatenated signature peptides encoded by QconCAT genes. Pratt JM, et al. Nat Protoc . 2006, 1 :1029-43.

Construct an artificial protein containing many peptides
At least one from each protein of interest
Ensure that the artificial protein is isotopically-labelled

Numerous absolute protein quantitations can be performed simultaneously

… from instrument to browser
From an QconCAT informatics perspective, there are three steps …
Selection of QconCAT peptides
Analysis and submission of data
Browsing / querying

Selection of QconCAT peptides
Q. Given a given protein, which peptides are suitable candidates for QconCAT peptides?
Must…
Be unique across organism
Be detectable (digestible, flyable)
Preferably…
Be unmodified

QconCAT Selection Wizard
Takes protein accession numbers as input (and other parameters)
Provides list of potential QconCAT peptides
Downloads sequence
Performs BLAST against species-specific UniProt (tests uniqueness)
Filters peptides “appropriately”
Applies score to peptide, using PeptideSieve (predict flyability)
Computational prediction of proteotypic peptides for quantitative proteomics. Mallick P, et al. Nat Biotechnol . 2007, 25 :125-31.

QconCAT… Multiplexed absolute quantification for proteomics using concatenated signature peptides encoded by QconCAT genes. Pratt JM, et al. Nature Protocols 1, 1029-1043 (2006)

QconCAT data analysis
Identify and quantify peptides / proteins of interest
Generate results in standard data format
Facilitates data sharing
Exploit existing software tools
PRIDE XML
PRoteomics IDEntifications
Community developed standard
http://www.ebi.ac.uk/pride/

QconCAT data analysis eXist database PRIDE XML Identify QconCAT Pride Wizard Quantify Format Upload Web / web service Browser Mascot PRIDE XML PRIDE Converter mzData

Pride Converter
Pride Converter (EBI) used to extract meta-data
Who ran the sample, what was the sample, instrument used? etc.
http://code.google.com/p/pride-converter/
PRIDE Converter: making proteomics data-sharing easy. Barsnes H, et al. Nat Biotechnol . 2009, 27 :598-9.
Simple wizard allowing experimental data to be marked up with meta-data

Pride Converter

QconCAT PrideWizard: Identify
Goal: to identify heavily-labelled QconCAT peptides
Uses Mascot
http://www.matrixscience.com/search_form_select.html
De facto standard database search engine for identifying peptides / proteins

QconCAT PrideWizard: Identify
Mascot results are parsed to find labelled QconCAT peptides:

QconCAT PrideWizard: Quantify
Goal: to quantify heavily-labelled QconCAT peptides
We now know m/z and retention time of peak identified as a QconCAT peptide
First step: extract mass chromatogram for both heavy (labelled) and light (unlabelled) peptide

Extracted mass chromatograms
Heavy and light peptide should overlay as they should have same retention time

Could use peak areas to quantify heavy versus light
BUT hard (and inaccurate) to determine start and end

Alternative: extract individual scans showing isotopic clusters for both heavy and light

Apply sliding window and plot heavy versus light:

Final step: apply linear regression to determine heavy:light ratio (and an error ):

MCISB Proteome Database
Searchable repository of quantitative proteomics data
Geeky bit…
eXist native XML database holding PRIDE XML
JSP front end
Querying extensible through XQuery
Web and web-service interface
Both human and computer-queryable

QconCAT informatics pipeline
Reference:
A QconCAT informatics pipeline for the analysis, visualization and sharing of absolute quantitative proteomics data. Swainston N, et al. Proteomics . 2011, 11 :329-33.

Data Integration

Systems biology modelling Enzyme kinetics Quantitative metabolomics Quantitative proteomics Systems Biology Model Parameters (K M , K cat ) Variables (metabolite, protein concentrations) PRIDE XML MeMo SABIO-RK Web service Web service Web service MeMo-RK Web service

Modelling life-cycle workflows

From experiment to simulation Kinetic models Experimental data Systematic integration of experimental data and models in systems biology. Li P, et al. BMC Bioinformatics . 2010, 11 :582.

Conclusion
An informatics pipeline has been developed for analysis of quantitative proteomics data
Data is associated with metadata , identified , quantified , and uploaded to database
Community standards have been followed
Experimental data can be incorporated in systems biology models
Allows simulations of biological systems to be performed

Thanks…

Data Integration, Mass Spectrometry Proteomics Software Development

by Neil Swainston

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